Why Display’s Moneyball Event Hasn’t Happened…Yet

I recently went onto Quora to notice someone had asked the question that is the bane of my existence: “What are the barriers to widespread adoption of dynamic display ad platforms and formats?” Folks provided great answers and I’ve hinted to a few solutions in my previous columns, but it’s important to really attack those […]

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Moneyball ShutterstockI recently went onto Quora to notice someone had asked the question that is the bane of my existence: “What are the barriers to widespread adoption of dynamic display ad platforms and formats?” Folks provided great answers and I’ve hinted to a few solutions in my previous columns, but it’s important to really attack those barriers given the results we’ve seen like:

  • Data-driven dynamic creative can increase return on advertising spend (ROAS) anywhere between 2 to 20 times
  • Almost all indications of user sentiment to personalized/relevant ads is very positive (minus a few incidents of annoying ads that won’t go away like here and here)

So, in summary, we’re delivering both better user experience and better performance for the advertiser. Anyone rational outside of our industry would ask, “So, everyone’s doing this, right?” Alas, this is not so.

In the best-selling book, Moneyball, Oakland A’s general manager Billy Beane was in a tough spot. The team had one of the lowest payrolls in Major League Baseball and was already destined to be near last place, so he made the controversial decision to apply a special form of statistics to valuing players.  From 2000 to 2003, the A’s made it to the playoffs despite their anemic payroll. Today, Billy’s methodologies for valuing players are par for the course.

I draw a lot of parallels between Billy’s situation and the display ad landscape today. Billy was able to produce significantly better results with a disruptive technology or method. In Billy’s world, once everyone saw it work, everyone jumped on it to keep competitive. You’d think the same would hold true given the results we’ve seen with data-driven dynamic creative, so what gives?

Left Brain, Right Brain Problem

For dynamic creative to be designed properly, proper data utilization is key to drive results. Whether your creative is rules-based (e.g. “Show the closest store if the user is within 10 miles”) or dynamically optimized (e.g. “Explore and exploit best performing based on audience data in real-time”), this requires some technical knowledge of the data available and its application. This tends to be the realm of quantitative market researchers, marketing analysts, etc. — the “left brain”.

On the flip side, good creative agencies hire creative people. This is not to say that creative people can’t also be technical, but unless that graphics designer or front-end user experience designer has specifically received technical training, data-powered dynamic creative won’t make sense. They’re “right brain” people.

In essence, we’ve given creative agencies an incredible tool to drive the strategic direction of a campaign with little to no instruction on how that tool can be used. Most of us (myself included) in the position to educate and inform have done a pretty poor job of putting forth resources.

N.B. Most of the mythology around the right hemisphere of the brain as the creative side and left hemisphere being the analytical has been debunked, but it still serves as a useful analogy for my purposes.

The Broken Workflow

In the current workflow, the media agency designs the media plan. The media plan goes to the creative agency to design creative for the audiences selected on the media plan and so on. Unfortunately, designing good dynamic creative should be done while the media plan is constructed. Dynamic creative opens up possibilities that aren’t available otherwise.

As an example, if you’re a quick serve restaurant with thousands of locations and you want to run an ad that shows the closest location, is this possible without dynamic creative? Not really. No one in their right mind is going to design a media plan with thousands of lines. (In this example, localizing the ad should create a discussion around the granularity and quality of the available user geo data, but this points to my left brain right brain problem above where the creative agency needs to have the technical knowledge to address the issue properly.) The creative agency should be at the table at the same time while the media plan is discussed.

Dynamic Creative Setup is Fragmented and Slow

Several dynamic creative players have touted their self-service interfaces and ability to quickly launch campaigns. However, with speed, you usually lose flexibility. Even if the interface allows for flexibility, then you’re back to the speed problem. I’ve seen a campaign using non-dynamic creative assets take as little as two days to launch.

Today, launching a data-powered dynamic creative campaign in that short a period is not possible unless it’s reusing pre-built components or conforms to a template’s tight parameters. The good news is that dynamic creative companies are trying to solve this problem, right now, because it’s a clear issue to adoption. By being slow or inflexible, it automatically locks you out of a fair amount of available budget.

When we get past these three big issues, I believe we will see dynamic creative disrupt display at a massive scale. It’s a fact that consumers change preferences to brands and products through the influence of a variety of factors. In display, we have the ability to evolve the campaign with these changes, but it needs to happen at all layers of the campaign: targeting, bidding, creative, and measurement.

We’re already making great progress at disrupting the targeting and bidding world with real-time bidding, but are only getting started with the others. Dynamic creative is real-time creative. We’re on the brink. It took over 100 years of professional baseball for Billy Beane to come along. As an industry, we can work together for our disruptive event without waiting 100 years.


Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.


About the author

Antony Chen
Contributor
Antony Chen is a product lead for optimization solutions at Yahoo!, which includes Smart Ads, Yahoo!'s market-leading solution for data-driven dynamic creative. Prior to Yahoo!, he spent 13 years in IT consulting focusing on program management, requirements gathering, and software development lifecycle methodologies.

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